Product details:
| ISBN13: | 9781032213637 |
| ISBN10: | 1032213639 |
| Binding: | Paperback |
| No. of pages: | 252 pages |
| Size: | 234x156 mm |
| Weight: | 470 g |
| Language: | English |
| Illustrations: | 78 Illustrations, black & white; 2 Halftones, black & white; 76 Line drawings, black & white; 5 Tables, black & white |
| 675 |
Category:
Digital Twin
A Dynamic System and Computing Perspective
Edition number: 1
Publisher: CRC Press
Date of Publication: 29 November 2024
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Publisher's listprice:
GBP 45.99
GBP 45.99
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Short description:
This book introduces the computing, mathematical and engineering background to understand and develop the concept of the digital twin. It provides background in modeling/simulation, computing technology, sensor/actuators, and so forth, needed to develop the next generation of digital twins.
Long description:
The digital twin of a physical system is an adaptive computer analog which exists in the cloud and adapts to changes in the physical system dynamically. This book introduces the computing, mathematical, and engineering background to understand and develop the concept of the digital twin. It provides background in modeling/simulation, computing technology, sensor/actuators, and so forth, needed to develop the next generation of digital twins. Concepts on cloud computing, big data, IoT, wireless communications, high-performance computing, and blockchain are also discussed.
Features:
- Provides background material needed to understand digital twin technology
- Presents computational facet of digital twin
- Includes physics-based and surrogate model representations
- Addresses the problem of uncertainty in measurements and modeling
- Discusses practical case studies of implementation of digital twins, addressing additive manufacturing, server farms, predictive maintenance, and smart cities
This book is aimed at graduate students and researchers in Electrical, Mechanical, Computer, and Production Engineering.
Table of Contents:
1. Introduction and Background. 2. Computing and Digital Twin. 3. Dynamic Systems. 4. Stochastic Analysis. 5. Digital Twin of Dynamic Systems. 6. Machine learning and Surrogate Models. 7. Surrogate based digital twin of dynamic system. 8. Digital Twin at Multiple Time Scales. 9. Digital twin of nonlinear MDOF systems.
